An Aspects Framework for Component-Based Requirements Prediction and Regression Testing

Abstract

Component-based software development has become more popular in recent decades. Currently, component delivery only includes interface specifications, which complicates the selection and integration of suitable components to build a new system. The majority of the components are reused, after appropriate modifications in accordance with the new system, or new version of the system. After components integration, errors may occur during the interaction of their features due to incomplete, ambiguous, or mismatched terms used in requirement analysis and specification, affecting component validation. Therefore, there is a need for a study that identifies challenges and covert concepts into practice by providing solutions to these challenges. The objective of this study is to identify some attributes and information sources that are essential during component-based development. The proposed framework is based on these attributes and information sources. In this study, we provide a taxonomy of attributes and information sources among different activities of component development, and propose a framework to improve the component development process. To investigate the proposed framework, we performed an experimental study to get real-world scenario results from industrial practitioners. The results showed that the proposed framework improves the process of component specification and validation without ambiguity and component failures. Additionally, compared with other methods (random priority, clustering-based and execution rate), the proposed framework successfully outperforms other methods. As a result, the proposed framework’s accuracy, F-measures, and fault identification rate were higher (i.e., greater than 80%) than those of other methods (i.e., less than 80%). The proposed framework will provide a significant guideline for practitioners and researchers.